Bump version to 0.1.1

.bumpversion.toml

@@ -0,0 +1,21 @@
+[tool.bumpversion]
+current_version = "0.1.1"
+parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)"
+serialize = ["{major}.{minor}.{patch}"]
+search = "{current_version}"
+replace = "{new_version}"
+regex = false
+ignore_missing_version = false
+ignore_missing_files = false
+tag = false
+sign_tags = false
+tag_name = "v{new_version}"
+tag_message = "Bump version: {current_version} → {new_version}"
+allow_dirty = false
+commit = false
+message = "Bump version: {current_version} → {new_version}"
+moveable_tags = []
+commit_args = ""
+setup_hooks = []
+pre_commit_hooks = []
+post_commit_hooks = []

ai_frame_image_server.py

@@ -9,8 +9,7 @@ import os
 import time
 import threading
 from apscheduler.schedulers.background import BackgroundScheduler
-# from lib import create_image, load_config, create_prompt_on_openwebui, cancel_current_job, get_prompt_from_png
-from libs.generic import load_config, load_recent_prompts, get_prompt_from_png
+from libs.generic import load_config, load_recent_prompts, get_details_from_png
 from libs.comfyui import cancel_current_job, create_image
 from libs.ollama import create_prompt_on_openwebui
 
@@ -29,7 +28,7 @@ def index() -> str:
     image_filename = "./image.png"
     image_path = os.path.join(image_folder, image_filename)
 
-    prompt = get_prompt_from_png(image_path)
+    prompt = get_details_from_png(image_path)["p"]
 
     return render_template(
         "index.html",
@@ -37,25 +36,28 @@ def index() -> str:
         prompt=prompt,
         reload_interval=user_config["frame"]["reload_interval"],
     )
-    
-    
+
 @app.route("/images", methods=["GET"])
 def gallery() -> str:
-    """
-    Renders the gallery HTML template.
-    Returns:
-        str: The rendered HTML template.
-    """
     images = []
     for f in os.listdir(image_folder):
         if f.lower().endswith(('png', 'jpg', 'jpeg', 'gif')):
-            path = os.path.join(image_folder, f)  # Full path to the image
-            prompt = get_prompt_from_png(path)  # Your method to extract the prompt
-            images.append({'filename': f, 'prompt': prompt, 'path': path})  # Add 'path' to the dictionary
-
-    images = sorted(images, key=lambda x: os.path.getmtime(x['path']), reverse=True)
+            images.append({'filename': f})
+    images = sorted(images, key=lambda x: os.path.getmtime(os.path.join(image_folder, x['filename'])), reverse=True)
     return render_template("gallery.html", images=images)
+    
 
+@app.route("/image-details/<filename>", methods=["GET"])
+def image_details(filename):
+    path = os.path.join(image_folder, filename)
+    if not os.path.exists(path):
+        return {"error": "File not found"}, 404
+    details = get_details_from_png(path)
+    return {
+        "prompt": details["p"],
+        "model": details["m"]
+    }
+    
 
 @app.route('/images/thumbnails/<path:filename>')
 def serve_thumbnail(filename):
@@ -103,7 +105,6 @@ def create() -> str:
         create_image(prompt)
 
     threading.Thread(target=create_image_in_background).start()
-    # return jsonify({"message": "Image creation started", "prompt": prompt if prompt else "Prompt will be generated"}), 200
     return render_template('image_queued.html', prompt=prompt)
 
 

lib.py

@@ -1,302 +0,0 @@
-# import random
-# import configparser
-# import logging
-# import sys
-# import litellm
-# import time
-# import os
-# import requests
-# from PIL import Image
-# from typing import Optional
-# from comfy_api_simplified import ComfyApiWrapper, ComfyWorkflowWrapper
-# from tenacity import (
-#     retry,
-#     stop_after_attempt,
-#     wait_fixed,
-#     before_log,
-#     retry_if_exception_type,
-# )
-# import nest_asyncio
-# import json
-# from datetime import datetime
-# from libs.create_thumbnail import generate_thumbnail
-# nest_asyncio.apply()
-
-# logging.basicConfig(level=logging.INFO)
-
-# LOG_FILE = "./prompts_log.jsonl"
-
-
-# def load_recent_prompts(count=7):
-#     recent_prompts = []
-
-#     try:
-#         with open(LOG_FILE, "r") as f:
-#             lines = f.readlines()
-#             for line in lines[-count:]:
-#                 data = json.loads(line.strip())
-#                 recent_prompts.append(data["prompt"])
-#     except FileNotFoundError:
-#         pass  # No prompts yet
-
-#     return recent_prompts
-
-
-# def save_prompt(prompt):
-#     entry = {"date": datetime.now().strftime("%Y-%m-%d"), "prompt": prompt}
-#     with open(LOG_FILE, "a") as f:
-#         f.write(json.dumps(entry) + "\n")
-
-
-
-# def get_available_models() -> list:
-#     """Fetches available models from ComfyUI."""
-#     url = user_config["comfyui"]["comfyui_url"] + "/object_info"
-#     response = requests.get(url)
-#     if response.status_code == 200:
-#         data = response.json()
-#         return (
-#             data.get("CheckpointLoaderSimple", {})
-#             .get("input", {})
-#             .get("required", {})
-#             .get("ckpt_name", [])[0]
-#         )
-#     else:
-#         print(f"Failed to fetch models: {response.status_code}")
-#         return []
-
-
-# def cancel_current_job() -> list:
-#     """Fetches available models from ComfyUI."""
-#     url = user_config["comfyui"]["comfyui_url"] + "/interrupt"
-#     response = requests.post(url)
-#     if response.status_code == 200:
-#         return "Cancelled"
-#     else:
-#         return "Failed to cancel"
-
-
-# def load_config() -> configparser.ConfigParser:
-#     """Loads user configuration from ./user_config.cfg."""
-#     user_config = configparser.ConfigParser()
-#     try:
-#         user_config.read("./user_config.cfg")
-#         logging.debug("Configuration loaded successfully.")
-#         return user_config
-#     except KeyError as e:
-#         logging.error(f"Missing configuration key: {e}")
-#         sys.exit(1)
-
-
-# def rename_image() -> str | None:
-#     """Renames 'image.png' in the output folder to a timestamped filename if it exists."""
-#     old_path = os.path.join(user_config["comfyui"]["output_dir"], "image.png")
-
-#     if os.path.exists(old_path):
-#         new_filename = f"{str(time.time())}.png"
-#         new_path = os.path.join(user_config["comfyui"]["output_dir"], new_filename)
-#         os.rename(old_path, new_path)
-#         generate_thumbnail(new_path)
-#         print(f"Renamed 'image.png' to '{new_filename}'")
-#         return new_filename
-#     else:
-#         print("No image.png found.")
-#         return None
-
-
-# def create_prompt_on_openwebui(prompt: str) -> str:
-#     """Sends prompt to OpenWebui and returns the generated response."""
-#     # Unique list of recent prompts
-#     recent_prompts = list(set(load_recent_prompts()))
-#     # Decide on whether to include a topic (e.g., 30% chance to include)
-#     topics = [t.strip() for t in user_config["comfyui"]["topics"].split(",") if t.strip()]
-#     topic_instruction = ""
-#     if random.random() < 0.3 and topics:
-#         selected_topic = random.choice(topics)
-#         topic_instruction = f" Incorporate the theme of '{selected_topic}' into the new prompt."
-
-#     user_content = (
-#         "Here are the prompts from the last 7 days:\n\n"
-#         + "\n".join(f"{i+1}. {p}" for i, p in enumerate(recent_prompts))
-#         + "\n\nDo not repeat ideas, themes, or settings from the above. "
-#         "Now generate a new, completely original Stable Diffusion prompt that hasn't been done yet."
-#         + topic_instruction
-#     )
-
-#     model = random.choice(user_config["openwebui"]["models"].split(","))
-#     response = litellm.completion(
-#         api_base=user_config["openwebui"]["base_url"],
-#         model="openai/" + model,
-#         messages=[
-#             {
-#                 "role": "system",
-#                 "content": (
-#                     "You are a prompt generator for Stable Diffusion. "
-#                     "Generate a detailed and imaginative prompt with a strong visual theme. "
-#                     "Focus on lighting, atmosphere, and artistic style. "
-#                     "Keep the prompt concise, no extra commentary or formatting."
-#                 ),
-#             },
-#             {
-#                 "role": "user",
-#                 "content": user_content,
-#             },
-#         ],
-#         api_key=user_config["openwebui"]["api_key"],
-#     )
-
-#     prompt = response["choices"][0]["message"]["content"].strip('"')
-#     # response = litellm.completion(
-#     #     api_base=user_config["openwebui"]["base_url"],
-#     #     model="openai/brxce/stable-diffusion-prompt-generator:latest",
-#     #     messages=[
-#     #         {
-#     #             "role": "user",
-#     #             "content": prompt,
-#     #         },
-#     #     ],
-#     #     api_key=user_config["openwebui"]["api_key"],
-#     # )
-#     # prompt = response["choices"][0]["message"]["content"].strip('"')
-#     logging.debug(prompt)
-#     return prompt
-
-
-# # Define the retry logic using Tenacity
-# @retry(
-#     stop=stop_after_attempt(3),
-#     wait=wait_fixed(5),
-#     before=before_log(logging.getLogger(), logging.DEBUG),
-#     retry=retry_if_exception_type(Exception),
-# )
-# def generate_image(
-#     file_name: str,
-#     comfy_prompt: str,
-#     workflow_path: str = "./workflow_api.json",
-#     prompt_node: str = "CLIP Text Encode (Prompt)",
-#     seed_node: str = "KSampler",
-#     seed_param: str = "seed",
-#     save_node: str = "Save Image",
-#     save_param: str = "filename_prefix",
-#     model_node: Optional[str] = "Load Checkpoint",
-#     model_param: Optional[str] = "ckpt_name",
-# ) -> None:
-#     """Generates an image using the Comfy API with configurable workflow settings."""
-#     try:
-#         api = ComfyApiWrapper(user_config["comfyui"]["comfyui_url"])
-#         wf = ComfyWorkflowWrapper(workflow_path)
-
-#         # Set workflow parameters
-#         wf.set_node_param(seed_node, seed_param, random.getrandbits(32))
-#         wf.set_node_param(prompt_node, "text", comfy_prompt)
-#         wf.set_node_param(save_node, save_param, file_name)
-#         wf.set_node_param(
-#             (
-#                 "Empty Latent Image"
-#                 if workflow_path.endswith("workflow_api.json")
-#                 else "CR Aspect Ratio"
-#             ),
-#             "width",
-#             user_config["comfyui"]["width"],
-#         )
-#         wf.set_node_param(
-#             (
-#                 "Empty Latent Image"
-#                 if workflow_path.endswith("workflow_api.json")
-#                 else "CR Aspect Ratio"
-#             ),
-#             "height",
-#             user_config["comfyui"]["height"],
-#         )
-
-#         # Conditionally set model if node and param are provided
-#         if model_node and model_param:
-#             if user_config["comfyui"].get("FLUX"):
-#                 valid_models = user_config["comfyui:flux"]["models"].split(",")
-#             else:
-#                 available_model_list = user_config["comfyui"]["models"].split(",")
-#                 valid_models = list(
-#                     set(get_available_models()) & set(available_model_list)
-#                 )
-
-#                 if not valid_models:
-#                     raise Exception("No valid models available.")
-
-#             model = random.choice(valid_models)
-#             wf.set_node_param(model_node, model_param, model)
-
-
-#         # Generate image
-#         logging.debug(f"Generating image: {file_name}")
-#         results = api.queue_and_wait_images(wf, save_node)
-#         rename_image()
-
-#         for _, image_data in results.items():
-#             output_path = os.path.join(
-#                 user_config["comfyui"]["output_dir"], f"{file_name}.png"
-#             )
-#             with open(output_path, "wb+") as f:
-#                 f.write(image_data)
-
-#         logging.debug(f"Image generated successfully for UID: {file_name}")
-
-#     except Exception as e:
-#         logging.error(f"Failed to generate image for UID: {file_name}. Error: {e}")
-#         raise
-
-
-# def create_image(prompt: str | None = None) -> None:
-#     """Main function for generating images."""
-#     if prompt is None:
-#         prompt = create_prompt_on_openwebui(user_config["comfyui"]["prompt"])
-
-#     if not prompt:
-#         logging.error("No prompt generated.")
-#         return
-#     save_prompt(prompt)
-
-#     use_flux = user_config["comfyui"].get("USE_FLUX", False)
-#     only_flux = user_config["comfyui"].get("ONLY_FLUX", False)
-
-#     selected_workflow = "SDXL"
-#     if use_flux:
-#         selected_workflow = "FLUX" if only_flux else random.choice(["FLUX", "SDXL"])
-
-#     if selected_workflow == "FLUX":
-#         # generate_image(
-#         #     file_name="image",
-#         #     comfy_prompt=prompt,
-#         #     workflow_path="./FLUX.json",
-#         #     prompt_node="Positive Prompt T5",
-#         #     seed_node="Seed",
-#         #     seed_param="seed",
-#         #     save_node="CivitAI Image Saver",
-#         #     save_param="filename",
-#         #     model_node="CivitAI Image Saver",
-#         #     model_param="modelname",
-#         # )
-#         print("flux")
-#     else:
-#         print("sdxl")
-#         # generate_image("image", prompt)
-
-#     logging.info(f"{selected_workflow} generation started with prompt: {prompt}")
-
-
-# def get_prompt_from_png(path):
-#     try:
-#         with Image.open(path) as img:
-#             try:
-#                 # Flux workflow
-#                 meta = json.loads(img.info["prompt"])['44']['inputs']['text']
-#             except KeyError:
-#                 # SDXL workflow
-#                 meta = json.loads(img.info["prompt"])['6']['inputs']['text']
-#             return meta or ""
-#     except Exception as e:
-#         print(f"Error reading metadata from {path}: {e}")
-#         return ""
-
-# user_config = load_config()
-# output_folder = user_config["comfyui"]["output_dir"]
-

libs/comfyui.py

@@ -63,7 +63,7 @@ def cancel_current_job() -> list:
 def generate_image(
     file_name: str,
     comfy_prompt: str,
-    workflow_path: str = "./workflow_api.json",
+    workflow_path: str = "./workflow_sdxl.json",
     prompt_node: str = "CLIP Text Encode (Prompt)",
     seed_node: str = "KSampler",
     seed_param: str = "seed",
@@ -84,7 +84,7 @@ def generate_image(
         wf.set_node_param(
             (
                 "Empty Latent Image"
-                if workflow_path.endswith("workflow_api.json")
+                if workflow_path.endswith("workflow_sdxl.json")
                 else "CR Aspect Ratio"
             ),
             "width",
@@ -93,7 +93,7 @@ def generate_image(
         wf.set_node_param(
             (
                 "Empty Latent Image"
-                if workflow_path.endswith("workflow_api.json")
+                if workflow_path.endswith("workflow_sdxl.json")
                 else "CR Aspect Ratio"
             ),
             "height",
@@ -157,7 +157,7 @@ def create_image(prompt: str | None = None) -> None:
         generate_image(
             file_name="image",
             comfy_prompt=prompt,
-            workflow_path="./FLUX.json",
+            workflow_path="./workflow_flux.json",
             prompt_node="Positive Prompt T5",
             seed_node="Seed",
             seed_param="seed",

libs/generic.py

@@ -63,16 +63,20 @@ def rename_image() -> str | None:
         return None
 
 
-def get_prompt_from_png(path):
+def get_details_from_png(path):
     try:
         with Image.open(path) as img:
             try:
                 # Flux workflow
-                meta = json.loads(img.info["prompt"])['44']['inputs']['text']
+                data = json.loads(img.info["prompt"])
+                prompt = data['44']['inputs']['text']
+                model = data['35']['inputs']['unet_name'].split(".")[0]
             except KeyError:
                 # SDXL workflow
-                meta = json.loads(img.info["prompt"])['6']['inputs']['text']
-            return meta or ""
+                data = json.loads(img.info["prompt"])
+                prompt = data['6']['inputs']['text']
+                model = data['4']['inputs']['ckpt_name']
+            return {"p":prompt,"m":model} or {"p":"","m":""}
     except Exception as e:
         print(f"Error reading metadata from {path}: {e}")
         return ""

templates/gallery.html

@@ -2,8 +2,8 @@
 <html lang="en">
 
 <head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1" />
     <title>Image Archive</title>
     <style>
         * {
@@ -124,65 +124,171 @@
         .button-link:hover {
             background: #555;
         }
+
+        @media (max-width: 600px) {
+            body {
+                padding: 1rem;
+                font-size: 14px;
+            }
+
+            .gallery {
+                grid-template-columns: repeat(auto-fill, minmax(250px, 1fr));
+                gap: 12px;
+            }
+
+            .gallery img {
+                border-radius: 8px;
+            }
+
+            .lightbox .close {
+                font-size: 36px;
+                top: 10px;
+                right: 15px;
+            }
+
+            .arrow {
+                font-size: 48px;
+                top: 50%;
+            }
+
+            #lightbox-prompt {
+                font-size: 14px;
+                max-width: 90%;
+                padding: 8px 16px;
+            }
+
+            .button-link {
+                font-size: 14px;
+                padding: 8px 16px;
+            }
+        }
     </style>
 </head>
 
 <body>
     <h1>Image Archive</h1>
-    <div class="gallery">
-        {% for image in images %}
-        <!-- <img src="{{ url_for('images', filename=image.thumbnail_filename) }}" alt="Image" loading="lazy" onclick="openLightbox({{ loop.index0 }})"> -->
-        <img src="{{ url_for('images', filename='thumbnails/' + image.filename) }}"
-            data-fullsrc="{{ url_for('images', filename=image.filename) }}" onclick="openLightbox({{ loop.index0 }})">
 
-        {% endfor %}
-    </div>
+    <!-- Empty gallery container; images will be loaded incrementally -->
+    <div class="gallery" id="gallery"></div>
+
     <div class="button-group">
         <a href="/" class="button-link">Back</a>
     </div>
 
-
     <!-- Lightbox -->
     <div class="lightbox" id="lightbox">
         <span class="close" onclick="closeLightbox()">&times;</span>
         <span class="arrow left" onclick="prevImage()">&#10094;</span>
-        <img id="lightbox-img" src="">
+        <img id="lightbox-img" src="" />
         <p id="lightbox-prompt"></p>
         <span class="arrow right" onclick="nextImage()">&#10095;</span>
     </div>
 
+    <!-- Pass image filenames from Flask to JS -->
     <script>
-        let images = [
+        const allImages = [
             {% for image in images %}
-        {
-            src: "{{ url_for('images', filename=image.filename) }}",
-                prompt: `{{ image.prompt | escape }}`
-        },
+        { filename: "{{ image.filename }}" },
         {% endfor %}
         ];
-        let currentIndex = 0;
+    </script>
 
-        function openLightbox(index) {
-            currentIndex = index;
-            <!-- document.getElementById("lightbox-img").src = images[currentIndex].src; -->
-            document.getElementById("lightbox-img").src = document.querySelectorAll('.gallery img')[currentIndex].dataset.fullsrc;
-            document.getElementById("lightbox-prompt").textContent = images[currentIndex].prompt;
+    <script>
+        const gallery = document.getElementById('gallery');
+        const batchSize = 6; // images to load per batch
+        let loadedCount = 0;
+        let currentIndex = 0;
+        const detailsCache = {};  // Cache for image details
+
+        function createImageElement(image) {
+            const img = document.createElement('img');
+            img.src = `/images/thumbnails/${image.filename}`;
+            img.dataset.fullsrc = `/images/${image.filename}`;
+            img.dataset.filename = image.filename;
+            img.loading = 'lazy';
+            img.style.cursor = 'pointer';
+            img.style.borderRadius = '10px';
+            img.addEventListener('click', () => openLightbox(img));
+            return img;
+        }
+
+        function loadNextBatch() {
+            const nextImages = allImages.slice(loadedCount, loadedCount + batchSize);
+            nextImages.forEach(image => {
+                const imgEl = createImageElement(image);
+                gallery.appendChild(imgEl);
+            });
+            loadedCount += nextImages.length;
+        }
+
+        // Load initial batch
+        loadNextBatch();
+
+        // Load more images when scrolling near bottom
+        window.addEventListener('scroll', () => {
+            if (loadedCount >= allImages.length) return; // all loaded
+            if ((window.innerHeight + window.scrollY) >= (document.body.offsetHeight - 100)) {
+                loadNextBatch();
+            }
+        });
+
+        // Get current images in gallery for lightbox navigation
+        function getGalleryImages() {
+            return Array.from(gallery.querySelectorAll('img'));
+        }
+
+        function openLightbox(imgEl) {
+            const images = getGalleryImages();
+            currentIndex = images.indexOf(imgEl);
+            showImageAndLoadDetails(currentIndex);
             document.getElementById("lightbox").style.display = "flex";
         }
 
+        function showImageAndLoadDetails(index) {
+            const images = getGalleryImages();
+            const imgEl = images[index];
+            const filename = imgEl.dataset.filename;
+            const fullsrc = imgEl.dataset.fullsrc;
+
+            document.getElementById("lightbox-img").src = fullsrc;
+
+            if (detailsCache[filename]) {
+                document.getElementById("lightbox-prompt").textContent =
+                    `Model: ${detailsCache[filename].model}\n\n${detailsCache[filename].prompt}`;
+            } else {
+                document.getElementById("lightbox-prompt").textContent = "Loading…";
+
+                fetch(`/image-details/${encodeURIComponent(filename)}`)
+                    .then(response => {
+                        if (!response.ok) throw new Error("Network response was not ok");
+                        return response.json();
+                    })
+                    .then(data => {
+                        detailsCache[filename] = data; // Cache the data
+                        document.getElementById("lightbox-prompt").textContent =
+                            `Model: ${data.model}\n\n${data.prompt}`;
+                    })
+                    .catch(() => {
+                        document.getElementById("lightbox-prompt").textContent = "Couldn’t load details.";
+                    });
+            }
+        }
+
+        function nextImage() {
+            const images = getGalleryImages();
+            currentIndex = (currentIndex + 1) % images.length;
+            showImageAndLoadDetails(currentIndex);
+        }
+
+        function prevImage() {
+            const images = getGalleryImages();
+            currentIndex = (currentIndex - 1 + images.length) % images.length;
+            showImageAndLoadDetails(currentIndex);
+        }
+
         function closeLightbox() {
             document.getElementById("lightbox").style.display = "none";
         }
-
-        function nextImage() {
-            currentIndex = (currentIndex + 1) % images.length;
-            openLightbox(currentIndex);
-        }
-
-        function prevImage() {
-            currentIndex = (currentIndex - 1 + images.length) % images.length;
-            openLightbox(currentIndex);
-        }
     </script>
 </body>